Physiological Role of AMPAR Nanoscale Organization at Basal State and During Synaptic Plasticities Benjamin Compans
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Behavioral Plasticity Through the Modulation of Switch Neurons
Behavioral Plasticity Through the Modulation of Switch Neurons Vassilis Vassiliades, Chris Christodoulou Department of Computer Science, University of Cyprus, 1678 Nicosia, Cyprus Abstract A central question in artificial intelligence is how to design agents ca- pable of switching between different behaviors in response to environmental changes. Taking inspiration from neuroscience, we address this problem by utilizing artificial neural networks (NNs) as agent controllers, and mecha- nisms such as neuromodulation and synaptic gating. The novel aspect of this work is the introduction of a type of artificial neuron we call \switch neuron". A switch neuron regulates the flow of information in NNs by se- lectively gating all but one of its incoming synaptic connections, effectively allowing only one signal to propagate forward. The allowed connection is determined by the switch neuron's level of modulatory activation which is affected by modulatory signals, such as signals that encode some informa- tion about the reward received by the agent. An important aspect of the switch neuron is that it can be used in appropriate \switch modules" in or- der to modulate other switch neurons. As we show, the introduction of the switch modules enables the creation of sequences of gating events. This is achieved through the design of a modulatory pathway capable of exploring in a principled manner all permutations of the connections arriving on the switch neurons. We test the model by presenting appropriate architectures in nonstationary binary association problems and T-maze tasks. The results show that for all tasks, the switch neuron architectures generate optimal adaptive behaviors, providing evidence that the switch neuron model could be a valuable tool in simulations where behavioral plasticity is required. -
Lettre Des Neurosciences / Lettreprintemps-ÉTÉ 2013 Numéro 44
la LA LETTRE DES NEUROSCIENCES / LettrePRINTEMPS-ÉTÉ 2013 NUMÉRO 44 Éditorial 3 Histoire des Neurosciences 4 Histoire récente des récepteurs aux neurotransmetteurs Dossier 8 Le sommeil dans tous ses états Nouveautés en neurosciences 24 La révolution de l’imagerie nanoscopique pour la neurobiologie cellulaire Tribune libre 28 Les neurosciences et le Droit Vie de la Société 31 Des métiers et des emplois pour les docteurs Comptes rendus colloques Changement de décor pour le secrétariat de la Société ! NUMÉRO 44 ISSN 2117-5535 La Lettre des Neurosciences est éditée par la Société des Neurosciences UUniversiténiversité BordeauxSegalen Bordeaux Segalen ·2 case · case 67 67 146, rue Léo-Léo-SaignatSaignat 33076 Bordeaux CCedexedex · France TTél.él. :: +(0)5+(0)557573740 57 57 37 40 | |Fax Fax : :+(0)5 +(0)5 57 57 57 57 3736 6950 [email protected] www.neurosciences.asso.fr Directeur de la publication-Rédacteur en Chef : YvesTillet | INRA - PRC - CNRS UMR 7 247 Univ. de Tours | IFCE Centre de Recherche de Tours 37380 Nouzilly | Fax : 02 47 42 77 43 [email protected] Fabrication : I. Conjat, J.-M. Israel, J.-F. Renaudon Concept maquette : Mazarine communication Comité de rédaction : J.-G. Barbara (Paris), D. Blum (Lille), C. Cleren (Rouen), A. Didier (Lyon), F. Eustache (Caen), S. Gaillard (Strasbourg), M. Garret (Bordeaux), J.-L. Gonzalez De Aguilar (Strasbourg), S. Pinto (Aix-en-Provence), A. Réaux-Le Goazigo (Paris). Ont participé à ce numéro : E. Audinat, B. Buisson, H. Chneiweiss, D. Choquet, J. Falcon, R. Garcia, I. Ghorayeb, C. Gronfier, A. Jean, M. Jouvet, P.-H. Luppi, A. -
The Question of Algorithmic Personhood and Being
Article The Question of Algorithmic Personhood and Being (Or: On the Tenuous Nature of Human Status and Humanity Tests in Virtual Spaces—Why All Souls Are ‘Necessarily’ Equal When Considered as Energy) Tyler Lance Jaynes Alden March Bioethics Institute, Albany Medical College, Albany, NY 12208, USA; [email protected] Abstract: What separates the unique nature of human consciousness and that of an entity that can only perceive the world via strict logic-based structures? Rather than assume that there is some potential way in which logic-only existence is non-feasible, our species would be better served by assuming that such sentient existence is feasible. Under this assumption, artificial intelligence systems (AIS), which are creations that run solely upon logic to process data, even with self-learning architectures, should therefore not face the opposition they have to gaining some legal duties and protections insofar as they are sophisticated enough to display consciousness akin to humans. Should our species enable AIS to gain a digital body to inhabit (if we have not already done so), it is more pressing than ever that solid arguments be made as to how humanity can accept AIS as being cognizant of the same degree as we ourselves claim to be. By accepting the notion that AIS can and will be able to fool our senses into believing in their claim to possessing a will or ego, we may yet Citation: Jaynes, T.L. The Question have a chance to address them as equals before some unforgivable travesty occurs betwixt ourselves of Algorithmic Personhood and Being and these super-computing beings. -
Correlating STED and Synchrotron XRF Nano-Imaging Unveils
TOOLS AND RESOURCES Correlating STED and synchrotron XRF nano-imaging unveils cosegregation of metals and cytoskeleton proteins in dendrites Florelle Domart1,2,3, Peter Cloetens4, Ste´ phane Roudeau1,2, Asuncion Carmona1,2, Emeline Verdier3, Daniel Choquet3,5†, Richard Ortega1,2†* 1Chemical Imaging and Speciation, CENBG, Univ. Bordeaux, Gradignan, France; 2CNRS, IN2P3, CENBG, UMR 5797, Gradignan, France; 3Univ. Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS, UMR 5297, Bordeaux, France; 4ESRF, the European Synchrotron, Grenoble, France; 5Univ. Bordeaux, CNRS, INSERM, Bordeaux Imaging Center, BIC, UMS, Bordeaux, France Abstract Zinc and copper are involved in neuronal differentiation and synaptic plasticity but the molecular mechanisms behind these processes are still elusive due in part to the difficulty of imaging trace metals together with proteins at the synaptic level. We correlate stimulated- emission-depletion microscopy of proteins and synchrotron X-ray fluorescence imaging of trace metals, both performed with 40 nm spatial resolution, on primary rat hippocampal neurons. We reveal the co-localization at the nanoscale of zinc and tubulin in dendrites with a molecular ratio of about one zinc atom per tubulin-ab dimer. We observe the co-segregation of copper and F-actin within the nano-architecture of dendritic protrusions. In addition, zinc chelation causes a decrease in the expression of cytoskeleton proteins in dendrites and spines. Overall, these results indicate *For correspondence: new functions for zinc and copper in the modulation of the cytoskeleton morphology in dendrites, a [email protected] mechanism associated to neuronal plasticity and memory formation. †These authors contributed equally to this work Competing interests: The Introduction authors declare that no The neurobiology of copper and zinc is a matter of intense investigation since they have been competing interests exist. -
A General Principle of Dendritic Constancy – a Neuron's Size And
bioRxiv preprint doi: https://doi.org/10.1101/787911; this version posted October 1, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Dendritic constancy Cuntz et al. A general principle of dendritic constancy – a neuron’s size and shape invariant excitability *Hermann Cuntza,b, Alexander D Birda,b, Marcel Beininga,b,c,d, Marius Schneidera,b, Laura Mediavillaa,b, Felix Z Hoffmanna,b, Thomas Dellerc,1, Peter Jedlickab,c,e,1 a Ernst Strungmann¨ Institute (ESI) for Neuroscience in cooperation with the Max Planck Society, 60528 Frankfurt am Main, Germany b Frankfurt Institute for Advanced Studies, 60438 Frankfurt am Main, Germany c Institute of Clinical Neuroanatomy, Neuroscience Center, Goethe University, 60590 Frankfurt am Main, Germany d Max Planck Insitute for Brain Research, 60438 Frankfurt am Main, Germany e ICAR3R – Interdisciplinary Centre for 3Rs in Animal Research, Justus Liebig University Giessen, 35390 Giessen, Germany 1 Joint senior authors *[email protected] Keywords Electrotonic analysis, Compartmental model, Morphological model, Excitability, Neuronal scaling, Passive normalisation, Cable theory 1/57 bioRxiv preprint doi: https://doi.org/10.1101/787911; this version posted October 1, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. -
Simulation and Analysis of Neuro-Memristive Hybrid Circuits
Simulation and analysis of neuro-memristive hybrid circuits João Alexandre da Silva Pereira Reis Mestrado em Física Departamento de Física e Astronomia 2016 Orientador Paulo de Castro Aguiar, Investigador Auxiliar do Instituto de Investigação e Inovação em Saúde da Universidade do Porto Coorientador João Oliveira Ventura, Investigador Auxiliar do Departamento de Física e Astronomia da Universidade do Porto Todas as correções determinadas pelo júri, e só essas, foram efetuadas. O Presidente do Júri, Porto, ______/______/_________ U P M’ P Simulation and analysis of neuro-memristive hybrid circuits Advisor: Author: Dr. Paulo A João Alexandre R Co-Advisor: Dr. João V A dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science A at A Department of Physics and Astronomy Faculty of Science of University of Porto II FCUP II Simulation and analysis of neuro-memristive hybrid circuits FCUP III Simulation and analysis of neuro-memristive hybrid circuits III Acknowledgments First and foremost, I need to thank my dissertation advisors Dr. Paulo Aguiar and Dr. João Ven- tura for their constant counsel, however basic my doubts were or which wall I ran into. Regardless of my stubbornness to stick to my way to research and write, they were always there for me. Of great importance, because of our shared goals, Catarina Dias and Mónica Cerquido helped me have a fixed and practical outlook to my research. During the this dissertation, I attended MemoCIS, a training school of memristors, which helped me have a more concrete perspective on state of the art research on technical details, modeling considerations and concrete proposed and realized applications. -
5. Neuromorphic Chips
Neuromorphic chips for the Artificial Brain Jaeseung Jeong, Ph.D Program of Brain and Cognitive Engineering, KAIST Silicon-based artificial intelligence is not efficient Prediction, expectation, and error Artificial Information processor vs. Biological information processor Core 2 Duo Brain • 65 watts • 10 watts • 291 million transistors • 100 billion neurons • >200nW/transistor • ~100pW/neuron Comparison of scales Molecules Channels Synapses Neurons CNS 0.1nm 10nm 1mm 0.1mm 1cm 1m Silicon Transistors Logic Multipliers PIII Parallel Gates Processors Motivation and Objective of neuromorphic engineering Problem • As compared to biological systems, today’s intelligent machines are less efficient by a factor of a million to a billion in complex environments. • For intelligent machines to be useful, they must compete with biological systems. Human Cortex Computer Simulation for Cerebral Cortex 20 Watts 1010 Watts 10 Objective I.4 Liter 4x 10 Liters • Develop electronic, neuromorphic machine technology that scales to biological level for efficient artificial intelligence. 9 Why Neuromorphic Engineering? Interest in exploring Interest in building neuroscience neurally inspired systems Key Advantages • The system is dynamic: adaptation • What if our primitive gates were a neuron computation? a synapse computation? a piece of dendritic cable? • Efficient implementations compute in their memory elements – more efficient than directly reading all the coefficients. Biology and Silicon Devices Similar physics of biological channels and p-n junctions -
Draft Nstac Report to the President On
THE PRESIDENT’S NATIONAL SECURITY TELECOMMUNICATIONS ADVISORY COMMITTEE DRAFT NSTAC REPORT TO THE PRESIDENT DRAFTon Communications Resiliency TBD Table of Contents Executive Summary .......................................................................................................ES-1 Introduction ........................................................................................................................1 Scoping and Charge.............................................................................................................2 Subcommittee Process ........................................................................................................3 Summary of Report Structure ...............................................................................................3 The Future State of ICT .......................................................................................................4 ICT Vision ...........................................................................................................................4 Wireline Segment ............................................................................................................5 Satellite Segment............................................................................................................6 Wireless 5G/6G ..............................................................................................................7 Public Safety Communications ..........................................................................................8 -
What Are Computational Neuroscience and Neuroinformatics? Computational Neuroscience
Department of Mathematical Sciences B12412: Computational Neuroscience and Neuroinformatics What are Computational Neuroscience and Neuroinformatics? Computational Neuroscience Computational Neuroscience1 is an interdisciplinary science that links the diverse fields of neu- roscience, computer science, physics and applied mathematics together. It serves as the primary theoretical method for investigating the function and mechanism of the nervous system. Com- putational neuroscience traces its historical roots to the the work of people such as Andrew Huxley, Alan Hodgkin, and David Marr. Hodgkin and Huxley's developed the voltage clamp and created the first mathematical model of the action potential. David Marr's work focused on the interactions between neurons, suggesting computational approaches to the study of how functional groups of neurons within the hippocampus and neocortex interact, store, process, and transmit information. Computational modeling of biophysically realistic neurons and dendrites began with the work of Wilfrid Rall, with the first multicompartmental model using cable theory. Computational neuroscience is distinct from psychological connectionism and theories of learning from disciplines such as machine learning,neural networks and statistical learning theory in that it emphasizes descriptions of functional and biologically realistic neurons and their physiology and dynamics. These models capture the essential features of the biological system at multiple spatial-temporal scales, from membrane currents, protein and chemical coupling to network os- cillations and learning and memory. These computational models are used to test hypotheses that can be directly verified by current or future biological experiments. Currently, the field is undergoing a rapid expansion. There are many software packages, such as NEURON, that allow rapid and systematic in silico modeling of realistic neurons. -
HOMOTECIA No. 3-12 Marzo 2014
HOMOTECIA Nº 3 – Año 12 Miércoles, 5 de Marzo de 2014 1 CALIDAD EDUCATIVA Y LA EVALUACIÓN DE LAS INSTITUCIONES. La UNESCO estableció mediante el Principio de no discriminación, el que “Todos los seres humanos deben tener acceso a la educación, tanto de derecho como de hecho” (1960). Con base en este principio, se crea en Ginebra (Suiza) en 1968 la fundación educativa Bachillerato Internacional® (BI), una organización sin fines de lucro. El BI tiene como objetivo ofrecer una educación de calidad para construir un mundo mejor, tal como lo manifiestan en la declaración de sus principios fundamentales. Consiste en la aplicación de tres programas distintos que abarcan desde la educación inicial hasta la preuniversitaria; estos son: El Programa de Educación Primaria (PEP), donde participan estudiantes con edades comprendidas entre los 3 y 10 años de edad; el Programa de los Años Intermedios (PAI), para estudiantes entre 11 y 16 años; y el Programa del Diploma (PD), para estudiantes NINA BARI entre los 17 y 19 años, cada uno con la misma filosofía: Construir un Mundo Mejor pero (1901 – 1961) siguiendo diferentes estrategias para conseguirlo. El Programa de Educación Primaria (PEP) busca el desarrollo integral del niño y de su capacidad para investigar y descubrir, Nació el 19 de noviembre de 1901, y murió el 15 de julio tanto en clase como en su entorno en general. El PEP compendia varias asignaturas, de de 1961, ambos momentos en Moscú, Rusia. características interdisciplinarias de importancia global, donde se fomenta la exploración y desarrollo de habilidades haciendo hincapié en el uso de la indagación como método de aprendizaje. -
Annual Report 20 14
ANNUAL REPORT 2014 HUMAN FRONTIER SCIENCE PROGRAM The Human Frontier Science Program is unique, supporting international collaboration to undertake innovative, risky, basic research at the frontier of the life sciences. Special emphasis is given to the support and training of independent young investigators, beginning at the postdoctoral level. The Program is implemented by an international organisation, supported financially by Australia, Canada, France, Germany, India, Italy, Japan, the Republic of Korea, New Zealand, Norway, Singapore, Switzerland, the United Kingdom, the United States of America, and the European Union. Since 1990, over 6000 awards have been made to researchers from more than 70 countries. Of these, 25 HFSP awardees have gone on to receive the Nobel Prize. APRIL 2014 - MARCH 2015 ANNUAL REPORT — 3 — Table of contents The following documents are available on the HFSP web site www.hfsp.org: Joint Communiqués (Tokyo 1992, Washington 1997, Berlin 2002, Bern 2004, Ottawa 2007, Canberra 2010, Brussels 2013): http://www.hfsp.org/about-us/governance/intergovernmental-conference Statutes of the International Human Frontier Science Program Organization : http://www.hfsp.org/about-us/governance/statutes Guidelines for the participation of new members in HFSPO : http://www.hfsp.org/about-us/new-membership General reviews of the HFSP (1996, 2001, 2006-2007, 2010): http://www.hfsp.org/about-us/reviews-hfsp Updated and previous lists of awards, including titles and abstracts: http://www.hfsp.org/awardees — 4 — INTRODUCTION Introduction -
The Electrotonic Transformation
Carnevale et al.: The Electrotonic Transformation Published as: Carnevale, N.T., Tsai, K.Y., Claiborne, B.J., and Brown, T.H.. The electrotonic transformation: a tool for relating neuronal form to function. In: Advances in Neural Information Processing Systems, vol. 7, eds. Tesauro, G., Touretzky, D.S., and Leen, T.K.. MIT Press, Cambridge, MA, 1995, pp. 69–76. The Electrotonic Transformation: a Tool for Relating Neuronal Form to Function Nicholas T. Carnevale Kenneth Y. Tsai Department of Psychology Department of Psychology Yale University Yale University New Haven, CT 06520 New Haven, CT 06520 Brenda J. Claiborne Thomas H. Brown Division of Life Sciences Department of Psychology University of Texas Yale University San Antonio, TX 79285 New Haven, CT 06520 Abstract The spatial distribution and time course of electrical signals in neurons have important theoretical and practical consequences. Because it is difficult to infer how neuronal form affects electrical signaling, we have developed a quantitative yet intuitive approach to the analysis of electrotonus. This approach transforms the architecture of the cell from anatomical to electrotonic space, using the logarithm of voltage attenuation as the distance metric. We describe the theory behind this approach and illustrate its use. Page 1 Carnevale et al.: The Electrotonic Transformation 1 INTRODUCTION The fields of computational neuroscience and artificial neural nets have enjoyed a mutually beneficial exchange of ideas. This has been most evident at the network level, where concepts such as massive parallelism, lateral inhibition, and recurrent excitation have inspired both the analysis of brain circuits and the design of artificial neural net architectures.